A huge ecosystem has been developed around the use of cookies on the Internet to track where people go online and the web sites visited by individuals, but a similar system to track the places visited by people in the physical world and the routes they travel to reach their destinations has yet to be developed. Online, the use of cookies has been widely recognized as critical to allow content providers to monetize more efficiently their web sites by delivering content, promotional offers, and advertising tailored to the demographics, potential profitability, and general profile of an individual as determined by the history of all web pages visited and clicked on, search history, and a large set of data derived from online behavior. Online, it is now very easy to know which sites have been visited and the browsing patterns and behavior and interest profile of most people. In the physical world, however, this capability is not as developed, and an implicit and indirect consumer benefit of using something like physical world tracking cookies has not been introduced. Location based technologies (e.g., GPS or network based location technologies derived from satellite, cellular, or Wi-Fi beacons) have allowed the delivery of content based on approximate (e.g., state/zip code) or precise location (e.g., GPS within 10-50 meters). Although location technologies provide much information for the delivery of various services, as well as content and advertising, real-time punctual location information still lacks additional data elements that could unlock rich new analytical capabilities that determine behavioral patterns and demographics. In the physical world (as in the online world) it is not enough to know where someone is, but one needs to know where that person has been before and where he or she is heading, the time of day, the frequency of routes travelled, and other factors such as correlation with demographics/profiles obtained online. Similarly, the ability to predict the profitability of those individuals for several products and services is dependent on knowing key components of their routes driven and their driving patterns in the physical world, such as, for example, speed, distance travelled, accumulated time and mileage driving, and neighborhood and malls visited. One possible solution could be to constantly track everyone (e.g., through their mobile devices), however the current state of the art has significant limitation as continuous tracking creates both technical obstacles (e.g., amount of data collected, wireless bandwidth utilization, and battery life) and privacy/authorization issues.